The present invention generally relates to telecommunication systems and methods, as well as automatic speech recognition systems. More particularly, the present invention pertains to machine learning within automatic speech recognition systems.
It is known in the art that speech recognition may be performed by measuring a system's ability to recognize a target word by analyzing its audio file with reference to another audio file(s) of a set of words. The target word may then be separated from the set of words if it does not meet a certain recognition threshold. By separating below-threshold target words from the set of words, the set may be restricted to readily-identified words. The words can thus be used in a speech recognition application with a certain degree of confidence. However this process can be time-consuming, and impractical in many applications. Having a system that can predict recognition accuracy of a target word, without the need for processing a large set of audio files to measure recognition rate, enables a user to understand how the system will perform in the real world without having to wait for a full deployment, thus saving money, effort, and resources.